Region-of-interest representations for electroanatomical mapping

ABSTRACT

A system for facilitating display of cardiac information includes a display device configured to present a cardiac map; and a processing unit configured to: receive electrical signals and indications of measurement locations corresponding to the electrical signals; generate, based on the electrical signals, the cardiac map, which includes annotations representing cardiac signal features; and determine a set of interesting cardiac signal features. The processing unit also may determine, based on the set of interesting cardiac signal features, a region of interest; and facilitate display, via the display device, of the cardiac map and a representation of the region of interest. The representation of the region of interest includes a first display parameter value that is different from a second display parameter value, where the second display parameter value is associated with at least one cardiac signal feature that is not included within the region of interest.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.10/537,261 filed on May 9, 2018, now U.S. patent Ser. No. 10/537,261,issued Jan. 21, 2020, which claims the benefit of ProvisionalApplication No. 62/504,301, filed May 10, 2017, which is hereinincorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates to medical systems and methods formapping an anatomical space of the body. More specifically, thedisclosure relates to systems and methods for cardiac mapping.

BACKGROUND

Use of minimally invasive procedures, such as catheter ablation, totreat a variety of heart conditions, such as supraventricular andventricular arrhythmias, is becoming increasingly more prevalent. Suchprocedures involve the mapping of electrical activity in the heart(e.g., based on cardiac signals), such as at various locations on theendocardium surface (“cardiac mapping”), to identify the site of originof the arrhythmia followed by a targeted ablation of the site. Toperform such cardiac mapping a catheter with one or more electrodes canbe inserted into the patient's heart chamber.

Conventional three-dimensional (3D) mapping techniques include contactmapping and non-contact mapping, and may employ a combination of contactand non-contact mapping. In both techniques, one or more catheters areadvanced into the heart. With some catheters, once in the chamber, thecatheter may be deployed to assume a 3D shape. In contact mapping,physiological signals resulting from the electrical activity of theheart are acquired with one or more electrodes located at the catheterdistal tip after determining that the tip is in stable and steadycontact with the endocardium surface of a particular heart chamber. Innon-contact-based mapping systems, using the signals detected by thenon-contact electrodes and information on chamber anatomy and relativeelectrode location, the system provides physiological informationregarding the endocardium of the heart chamber. Location and electricalactivity is usually measured sequentially on a point-by-point basis atabout 50 to 200 points on the internal surface of the heart to constructan electro-anatomical depiction of the heart. The generated map may thenserve as the basis for deciding on a therapeutic course of action, forexample, tissue ablation, to alter the propagation of the heart'selectrical activity and to restore normal heart rhythm.

In many conventional mapping systems, the clinician visually inspects orexamines the captured electrograms (EGMs), which increases examinationtime and cost. During an automatic electro-anatomical mapping process,however, approximately 6,000 to 20,000 intracardiac electrograms (EGMs)may be captured, which does not lend itself to being manually inspectedin full by a clinician (e.g., a physician) for a diagnostic assessment,EGM categorization, and/or the like. Typically mapping systems extractscalar values from each EGM to construct voltage, activation, or othermap types to depict overall patterns of activity within the heart. Whilemaps typically are generated for entire heart chambers, much of theclinical focus is often placed on specific, smaller, regions such as,for example, isthmi, scars, lines of block, and/or the like. User-drivenfocus is typically poorly facilitated by mapping systems, andcontext-preserving methods largely rely on mental imaging, which isheavily operator-dependent. Additionally, context-lossy methodstypically are not well tolerated by users and often result in proceduralnuisance and delay. Futhermore, data-driven (algorithm-supported) focusis largely absent from conventional mapping systems.

SUMMARY

In an Example 1, a system for facilitating display of cardiacinformation, the system comprising: a display device configured topresent a cardiac map; and a processing unit configured to: receive aplurality of electrical signals; receive an indication of a measurementlocation corresponding to each electrical signal of the plurality ofelectrical signals; generate, based on the plurality of electricalsignals, the cardiac map, the cardiac map comprising a plurality ofannotations representing a plurality of cardiac signal features;determine, from the plurality of cardiac signal features, a set ofinteresting cardiac signal features; determine, based on the set ofinteresting cardiac signal features, a region of interest; andfacilitate display, via the display device, of the cardiac map and arepresentation of the region of interest, the representation of theregion of interest comprising a first display parameter value that isdifferent from a second display parameter value, wherein the seconddisplay parameter value is associated with at least one cardiac signalfeature that is not included within the region of interest.

In an Example 2, the system of Example 1, wherein the processing unit isfurther configured to: determine, for each cardiac signal feature of theset of cardiac signal features, a radius of influence; and determine theregion of interest based on the determined radius of influence for eachcardiac signal feature.

In an Example 3, the system of Example 2, wherein the processing unit isconfigured to generate the cardiac map based on a mesh, and wherein theprocessing unit is further configured to: label each mesh vertex of amesh element of the mesh with a first value; label each mesh vertex ofthe mesh element of the mesh with second value if a criterion issatisfied; and facilitate display of the representation of the region ofinterest based on the mesh vertex labels.

In an Example 4, the system of Example 3, wherein the mesh comprises atriangular mesh, wherein the first value comprises a 0, and wherein thesecond value comprises a 1, and wherein the processing unit isconfigured to: determine the number of mesh vertices of the mesh elementthat are labeled with the second value; apply a highlighting effect, butno border effect, to the mesh element if the number of mesh vertices ofthe mesh element that are labeled with the second value is 3; apply aborder effect, but no highlighting effect, to the mesh element if thenumber of mesh vertices of the mesh element that are labeled with thesecond value is 2; and apply no border effect and no highlighting effectto the mesh element if the number of mesh vertices of the mesh elementthat are labeled with the second value is less than 2.

In an Example 5, the system of Example 2, wherein the processing unit isfurther configured to: determine a position of each model pixel;determine, for each model pixel, an influence subset of the set ofinteresting cardiac electrical signal features; determine, for eachmodel pixel, an influence force associated with each cardiac electricalsignal feature of the influence subset; determine, for each model pixel,a sum of the influence forces; compare, for each model pixel, the sum ofthe influence forces to a threshold; and apply a highlighting effect toeach model pixel if the sum of the influence forces exceeds thethreshold.

In an Example 6, the system of any of Examples 1-5, the cardiacelectrical signal feature comprising at least one of an activation time,a detected activation, a minimum voltage value, a maximum voltagesvalue, a maximum negative time-derivative of voltage, an instantaneouspotential, a voltage amplitude, a dominant frequency, and a peak-to-peakvoltage.

In an Example 7, the system of any of Examples 1-5, the displayparameter comprising color saturation.

In an Example 8, a system for facilitating display of cardiacinformation, the system comprising: a display device configured topresent a cardiac map; and a processing unit configured to: receive aplurality of electrical signals; receive an indication of a measurementlocation corresponding to each electrical signal of the plurality ofelectrical signals; generate, based on the plurality of electricalsignals, the cardiac map, the cardiac map comprising a plurality ofannotations representing a plurality of cardiac signal features;determine, from the plurality of cardiac signal features, a set ofinteresting cardiac signal features; determine, for each cardiac signalfeature of the set of cardiac signal features, a radius of influence;determine, based on the set of interesting cardiac signal features andthe corresponding radii of influence, a region of interest; andfacilitate display, via the display device, of the cardiac map and arepresentation of the region of interest.

In an Example 9, the system of Example 8, the representation of theregion of interest comprising a first color saturation value that isdifferent from a second color saturation value, wherein the second colorsaturation value is associated with at least one cardiac signal featurethat is not included within the region of interest.

In an Example 10, the system of either of Examples 8 or 9, the cardiacelectrical signal feature comprising at least one of an activation time,a detected activation, a minimum voltage value, a maximum voltagesvalue, a maximum negative time-derivative of voltage, an instantaneouspotential, a voltage amplitude, a dominant frequency, and a peak-to-peakvoltage.

In an Example 11, a method of presenting cardiac information, the methodcomprising: receiving a plurality of electrical signals; receiving anindication of a measurement location corresponding to each electricalsignal of the plurality of electrical signals; generating, based on theplurality of electrical signals, the cardiac map, the cardiac mapcomprising a plurality of annotations representing a plurality ofcardiac signal features; determining, from the plurality of cardiacsignal features, a set of interesting cardiac signal features;determining, based on the set of interesting cardiac signal features, aregion of interest; and facilitating display, via the display device, ofthe cardiac map and a representation of the region of interest, therepresentation of the region of interest comprising a first colorsaturation value that is different from a second color saturation value,wherein the second color saturation value is associated with at leastone cardiac signal feature that is not included within the region ofinterest.

In an Example 12, the method of Example 11, further comprising:determining, for each cardiac signal feature of the set of cardiacsignal features, a radius of influence; and determining the region ofinterest based on the determined radius of influence for each cardiacsignal feature.

In an Example 13, the method of either of Examples 11 or 12, furthercomprising generating the cardiac map based on a mesh, and wherein themethod further comprises: labeling each mesh vertex of a mesh element ofthe mesh with a first value; labeling each mesh vertex of the meshelement of the mesh with second value if a criterion is satisfied; andfacilitating display of the representation of the region of interestbased on the mesh vertex labels.

In an Example 14, the method of Example 12, further comprising:determining a position of each model pixel; determining, for each modelpixel, an influence subset of the set of interesting cardiac electricalsignal features; determining, for each model pixel, an influence forceassociated with each cardiac electrical signal feature of the influencesubset; determining, for each model pixel, a sum of the influenceforces; comparing, for each model pixel, the sum of the influence forcesto a threshold; and applying a highlighting effect to each model pixelif the sum of the influence forces exceeds the threshold.

In an Example 15, the method of any of Examples 11-14, the cardiacelectrical signal feature comprising at least one of an activation time,a detected activation, a minimum voltage value, a maximum voltagesvalue, a maximum negative time-derivative of voltage, an instantaneouspotential, a voltage amplitude, a dominant frequency, and a peak-to-peakvoltage.

In an Example 16, a system for facilitating display of cardiacinformation, the system comprising: a display device configured topresent a cardiac map; and a processing unit configured to: receive aplurality of electrical signals; receive an indication of a measurementlocation corresponding to each electrical signal of the plurality ofelectrical signals; generate, based on the plurality of electricalsignals, the cardiac map, the cardiac map comprising a plurality ofannotations representing a plurality of cardiac signal features;determine, from the plurality of cardiac signal features, a set ofinteresting cardiac signal features; determine, based on the set ofinteresting cardiac signal features, a region of interest; andfacilitate display, via the display device, of the cardiac map and arepresentation of the region of interest, the representation of theregion of interest comprising a first color saturation value that isdifferent from a second color saturation value, wherein the second colorsaturation value is associated with at least one cardiac signal featurethat is not included within the region of interest.

In an Example 17, the system of Example 16, wherein the processing unitis further configured to: determine, for each cardiac signal feature ofthe set of cardiac signal features, a radius of influence; and determinethe region of interest based on the determined radius of influence foreach cardiac signal feature.

In an Example 18, the system of Example 17, wherein the processing unitis configured to generate the cardiac map based on a mesh, and whereinthe processing unit is further configured to: label each mesh vertex ofa mesh element of the mesh with a first value; label each mesh vertex ofthe mesh element of the mesh with second value if a criterion issatisfied; and facilitate display of the representation of the region ofinterest based on the mesh vertex labels.

In an Example 19, the system of Example 18, wherein the mesh comprises atriangular mesh, wherein the first value comprises a 0, and wherein thesecond value comprises a 1, and wherein the processing unit isconfigured to: determine the number of mesh vertices of the mesh elementthat are labeled with the second value; apply a highlighting effect, butno border effect, to the mesh element if the number of mesh vertices ofthe mesh element that are labeled with the second value is 3; apply aborder effect, but no highlighting effect, to the mesh element if thenumber of mesh vertices of the mesh element that are labeled with thesecond value is 2; and apply no border effect and no highlighting effectto the mesh element if the number of mesh vertices of the mesh elementthat are labeled with the second value is less than 2.

In an Example 20, the system of Example 17, wherein the processing unitis further configured to: determine a position of each model pixel;determine, for each model pixel, an influence subset of the set ofinteresting cardiac electrical signal features; determine, for eachmodel pixel, an influence force associated with each cardiac electricalsignal feature of the influence subset; determine, for each model pixel,a sum of the influence forces; compare, for each model pixel, the sum ofthe influence forces to a threshold; and apply a highlighting effect toeach model pixel if the sum of the influence forces exceeds thethreshold.

In an Example 21, the system of Example 20, the representation of theregion of interest comprising a border, wherein the processing unit isfurther configured to: generate a scaled region of interest shapecorresponding to the region of interest; and generate the border byfacilitating display of the highlighted pixels above the scaled regionof interest shape.

In an Example 22, the system of Example 16, the cardiac electricalsignal feature comprising at least one of an activation time, a detectedactivation, a minimum voltage value, a maximum voltages value, a maximumnegative time-derivative of voltage, an instantaneous potential, avoltage amplitude, a dominant frequency, and a peak-to-peak voltage.

In an Example 23, a system for facilitating display of cardiacinformation, the system comprising: a display device configured topresent a cardiac map; and a processing unit configured to: receive aplurality of electrical signals; receive an indication of a measurementlocation corresponding to each electrical signal of the plurality ofelectrical signals; generate, based on the plurality of electricalsignals, the cardiac map, the cardiac map comprising a plurality ofannotations representing a plurality of cardiac signal features;determine, from the plurality of cardiac signal features, a set ofinteresting cardiac signal features; determine, for each cardiac signalfeature of the set of cardiac signal features, a radius of influence;determine, based on the set of interesting cardiac signal features andthe corresponding radii of influence, a region of interest; andfacilitate display, via the display device, of the cardiac map and arepresentation of the region of interest.

In an Example 24, the system of Example 23, the representation of theregion of interest comprising a first color saturation value that isdifferent from a second color saturation value, wherein the second colorsaturation value is associated with at least one cardiac signal featurethat is not included within the region of interest.

In an Example 25, the system of Example 23, wherein the processing unitis configured to generate the cardiac map based on a mesh, and whereinthe processing unit is further configured to: label each mesh vertex ofa mesh element of the mesh with a first value; label each mesh vertex ofthe mesh element of the mesh with second value if a criterion issatisfied; and facilitate display of the representation of the region ofinterest based on the mesh vertex labels.

In an Example 26, the system of Example 25, wherein the mesh comprises atriangular mesh, wherein the first value comprises a 0, and wherein thesecond value comprises a 1, and wherein the processing unit isconfigured to: determine the number of mesh vertices of the mesh elementthat are labeled with the second value; apply a highlighting effect, butno border effect, to the mesh element if the number of mesh vertices ofthe mesh element that are labeled with the second value is 3; apply aborder effect, but no highlighting effect, to the mesh element if thenumber of mesh vertices of the mesh element that are labeled with thesecond value is 2; and apply no border effect and no highlighting effectto the mesh element if the number of mesh vertices of the mesh elementthat are labeled with the second value is less than 2.

In an Example 27, the system of Example 23, wherein the processing unitis further configured to: determine a position of each model pixel;determine, for each model pixel, an influence subset of the set ofinteresting cardiac electrical signal features; determine, for eachmodel pixel, an influence force associated with each cardiac electricalsignal feature of the influence subset; determine, for each model pixel,a sum of the influence forces; compare, for each model pixel, the sum ofthe influence forces to a threshold; and apply a highlighting effect toeach model pixel if the sum of the influence forces exceeds thethreshold.

In an Example 28, the system of Example 23, the cardiac electricalsignal feature comprising at least one of an activation time, a detectedactivation, a minimum voltage value, a maximum voltages value, a maximumnegative time-derivative of voltage, an instantaneous potential, avoltage amplitude, a dominant frequency, and a peak-to-peak voltage.

In an Example 29, a method of presenting cardiac information, the methodcomprising: receiving a plurality of electrical signals; receiving anindication of a measurement location corresponding to each electricalsignal of the plurality of electrical signals; generating, based on theplurality of electrical signals, the cardiac map, the cardiac mapcomprising a plurality of annotations representing a plurality ofcardiac signal features; determining, from the plurality of cardiacsignal features, a set of interesting cardiac signal features;determining, based on the set of interesting cardiac signal features, aregion of interest; and facilitating display, via the display device, ofthe cardiac map and a representation of the region of interest, therepresentation of the region of interest comprising a first colorsaturation value that is different from a second color saturation value,wherein the second color saturation value is associated with at leastone cardiac signal feature that is not included within the region ofinterest.

In an Example 30, the method of Example 29, further comprising:determining, for each cardiac signal feature of the set of cardiacsignal features, a radius of influence; and determining the region ofinterest based on the determined radius of influence for each cardiacsignal feature.

In an Example 31, the method of Example 29, further comprisinggenerating the cardiac map based on a mesh, and wherein the methodfurther comprises: labeling each mesh vertex of a mesh element of themesh with a first value; labeling each mesh vertex of the mesh elementof the mesh with second value if a criterion is satisfied; andfacilitating display of the representation of the region of interestbased on the mesh vertex labels.

In an Example 32, the method of Example 31, wherein the mesh comprises atriangular mesh, wherein the first value comprises a 0, and wherein thesecond value comprises a 1, the method further comprising: determiningthe number of mesh vertices of the mesh element that are labeled withthe second value; applying a highlighting effect, but no border effect,to the mesh element if the number of mesh vertices of the mesh elementthat are labeled with the second value is 3; applying a border effect,but no highlighting effect, to the mesh element if the number of meshvertices of the mesh element that are labeled with the second value is2; and applying no border effect and no highlighting effect to the meshelement if the number of mesh vertices of the mesh element that arelabeled with the second value is less than 2.

In an Example 33, the method of Example 29, further comprising:determining a position of each model pixel; determining, for each modelpixel, an influence subset of the set of interesting cardiac electricalsignal features; determining, for each model pixel, an influence forceassociated with each cardiac electrical signal feature of the influencesubset; determining, for each model pixel, a sum of the influenceforces; comparing, for each model pixel, the sum of the influence forcesto a threshold; and applying a highlighting effect to each model pixelif the sum of the influence forces exceeds the threshold.

In an Example 34, the method of Example 33, the representation of theregion of interest comprising a border, wherein the processing unit isfurther configured to: generate a scaled region of interest shapecorresponding to the region of interest; and generate the border byfacilitating display of the highlighted pixels above the scaled regionof interest shape.

In an Example 35, the method of Example 29, the cardiac electricalsignal feature comprising at least one of an activation time, a detectedactivation, a minimum voltage value, a maximum voltages value, a maximumnegative time-derivative of voltage, an instantaneous potential, avoltage amplitude, a dominant frequency, and a peak-to-peak voltage.

While multiple embodiments are disclosed, still other embodiments of thepresently disclosed subject matter will become apparent to those skilledin the art from the following detailed description, which shows anddescribes illustrative embodiments of the disclosed subject matter.Accordingly, the drawings and detailed description are to be regarded asillustrative in nature and not restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual schematic diagram depicting an illustrativecardiac mapping system, in accordance with embodiments of the subjectmatter disclosed herein.

FIG. 2 is a block diagram depicting an illustrative processing unit, inaccordance with embodiments of the subject matter disclosed herein.

FIGS. 3A and 3B depict illustrative cardiac maps, in accordance withembodiments of the subject matter disclosed herein.

FIG. 4 is a flow diagram depicting an illustrative process forgenerating a cardiac map, in accordance with embodiments of the subjectmatter disclosed herein.

FIG. 5 is a flow diagram depicting an illustrative method of processingelectrophysiological information, in accordance with embodiments of thesubject matter disclosed herein.

FIG. 6 is a flow diagram depicting an illustrative method of generatinga representation of a region of interest, in accordance with embodimentsof the subject matter disclosed herein.

FIG. 7 is a conceptual schematic diagram depicting an illustrativeexample of generating a representation of a region of interest, usingaspects of embodiments of the method depicted in FIG. 6, in accordancewith embodiments of the subject matter disclosed herein.

FIG. 8 is a flow diagram depicting an illustrative method of generatinga representation of a region of interest, in accordance with embodimentsof the subject matter disclosed herein.

FIG. 9 is a conceptual schematic diagram depicting an illustrativeexample of generating a representation of a region of interest, usingaspects of embodiments of the method depicted in FIG. 8, in accordancewith embodiments of the subject matter disclosed herein.

FIGS. 10A-10C are conceptual schematic diagrams depicting anillustrative example of generating a border of a representation of aregion of interest, in accordance with embodiments of the subject matterdisclosed herein.

While the disclosed subject matter is amenable to various modificationsand alternative forms, specific embodiments have been shown by way ofexample in the drawings and are described in detail below. Theintention, however, is not to limit the disclosure to the particularembodiments described. On the contrary, the disclosure is intended tocover all modifications, equivalents, and alternatives falling withinthe scope of the disclosure as defined by the appended claims.

As the terms are used herein with respect to measurements (e.g.,dimensions, characteristics, attributes, components, etc.), and rangesthereof, of tangible things (e.g., products, inventory, etc.) and/orintangible things (e.g., data, electronic representations of currency,accounts, information, portions of things (e.g., percentages,fractions), calculations, data models, dynamic system models,algorithms, parameters, etc.), “about” and “approximately” may be used,interchangeably, to refer to a measurement that includes the statedmeasurement and that also includes any measurements that are reasonablyclose to the stated measurement, but that may differ by a reasonablysmall amount such as will be understood, and readily ascertained, byindividuals having ordinary skill in the relevant arts to beattributable to measurement error; differences in measurement and/ormanufacturing equipment calibration; human error in reading and/orsetting measurements; adjustments made to optimize performance and/orstructural parameters in view of other measurements (e.g., measurementsassociated with other things); particular implementation scenarios;imprecise adjustment and/or manipulation of things, settings, and/ormeasurements by a person, a computing device, and/or a machine; systemtolerances; control loops; machine-learning; foreseeable variations(e.g., statistically insignificant variations, chaotic variations,system and/or model instabilities, etc.); preferences; and/or the like.

Although the term “block” may be used herein to connote differentelements illustratively employed, the term should not be interpreted asimplying any requirement of, or particular order among or between,various blocks disclosed herein. Similarly, although illustrativemethods may be represented by one or more drawings (e.g., flow diagrams,communication flows, etc.), the drawings should not be interpreted asimplying any requirement of, or particular order among or between,various steps disclosed herein. However, certain embodiments may requirecertain steps and/or certain orders between certain steps, as may beexplicitly described herein and/or as may be understood from the natureof the steps themselves (e.g., the performance of some steps may dependon the outcome of a previous step). Additionally, a “set,” “subset,” or“group” of items (e.g., inputs, algorithms, data values, etc.) mayinclude one or more items, and, similarly, a subset or subgroup of itemsmay include one or more items. A “plurality” means more than one.

As used herein, the term “based on” is not meant to be restrictive, butrather indicates that a determination, identification, prediction,calculation, and/or the like, is performed by using, at least, the termfollowing “based on” as an input. For example, predicting an outcomebased on a particular piece of information may additionally, oralternatively, base the same determination on another piece ofinformation.

DETAILED DESCRIPTION

Embodiments of systems and methods described herein facilitateprocessing sensed cardiac electrical signals to present a representationof a region of interest (ROI) on an electroanatomical map. Inembodiments, representations of ROIs may facilitate clear visualdistinction of the ROI while preserving the context of the annotations.Representations of ROIs may include highlighting effects applied to amap that are persistent, tolerant to view angles, tolerant to variouszoom levels, and do not obstruct other information in the map. Inembodiments, for example, a representation of an ROI may include abordered, highlighted overlay of a corresponding portion of the surfaceof the map on top of a de-saturated map. In embodiments, renderingrepresentations of ROIs with borders may facilitate clearly presentingmultiple distinct ROIs (which may, in embodiments, be referred to asmultiple portions of an ROI). Embodiments of the highlighting operationsdescribed herein may be user driven and/or algorithm driven.

According to embodiments, to perform aspects of embodiments of themethods described herein, cardiac electrical signals may be obtainedfrom a mapping catheter (e.g., associated with a mapping system), arecording system, a coronary sinus (CS) catheter or other referencecatheter, an ablation catheter, a memory device (e.g., a local memory, acloud server, etc.), a communication component, a medical device (e.g.,an implantable medical device, an external medical device, a telemetrydevice, etc.), and/or the like.

As the term is used herein, a sensed cardiac electrical signal may referto one or more sensed signals. Each cardiac electrical signal mayinclude a number of intracardiac electrograms (EGMs) sensed within apatient's heart, and may include any number of features that may beascertained by aspects of the system 100. Examples of cardiac electricalsignal features include, but are not limited to, activation times,activations, activation waveforms, filtered activation waveforms,minimum voltage values, maximum voltages values, maximum negativetime-derivatives of voltages, instantaneous potentials, voltageamplitudes, dominant frequencies, peak-to-peak voltages, and/or thelike. A cardiac electrical signal feature may refer to one or morefeatures extracted from one or more cardiac electrical signals, derivedfrom one or more features that are extracted from one or more cardiacelectrical signals, and/or the like. Additionally, a representation, ona cardiac and/or a surface map, of a cardiac electrical signal featuremay represent one or more cardiac electrical signal features, aninterpolation of a number of cardiac electrical signal features, and/orthe like.

Each cardiac signal also may be associated with a set of respectiveposition coordinates that corresponds to the location at which thecardiac electrical signal was sensed. Each of the respective positioncoordinates for the sensed cardiac signals may include three-dimensionalCartesian coordinates, polar coordinates, and/or the like. Inembodiments, other coordinate systems can be used. In embodiments, anarbitrary origin is used and the respective position coordinates referto positions in space relative to the arbitrary origin. Since, inembodiments, the cardiac signals may be sensed on the cardiac surfaces,the respective position coordinates may be on the endocardial surface,epicardial surface, in the mid-myocardium of the patient's heart, and/orin the vicinity of one of one of these.

FIG. 1 shows a schematic diagram of an exemplary embodiment of a cardiacmapping system 100. As indicated above, embodiments of the subjectmatter disclosed herein may be implemented in a mapping system (e.g.,the mapping system 100), while other embodiments may be implemented inan ablation system, a recording system, a computer analysis system,and/or the like. The mapping system 100 includes a moveable catheter 110having multiple spatially distributed electrodes. During asignal-acquisition stage of a cardiac mapping procedure, the catheter110 is displaced to multiple locations within the heart chamber intowhich the catheter 110 is inserted. In some embodiments the distal endof the catheter 110 is fitted with multiple electrodes spread somewhatuniformly over the catheter. For example, the electrodes may be mountedon the catheter 110 following a 3D olive shape, a basket shape, and/orthe like. The electrodes are mounted on a device capable of deployingthe electrodes into the desired shape while inside the heart, andretracting the electrodes when the catheter is removed from the heart.To allow deployment into a 3D shape in the heart, electrodes may bemounted on a balloon, shape memory material such as Nitinol, actuablehinged structure, and/or the like. According to embodiments, thecatheter 110 may be a mapping catheter, an ablation catheter, adiagnostic catheter, a CS catheter, and/or the like. For example,aspects of embodiments of the catheter 110, the electrical signalsobtained using the catheter 110, and subsequent processing of theelectrical signals, as described herein, may also be applicable inimplementations having a recording system, ablation system, and/or anyother system having a catheter with electrodes that may be configured toobtain cardiac electrical signals.

At each of the locations to which the catheter 110 is moved, thecatheter's multiple electrodes acquire signals resulting from theelectrical activity in the heart. Consequently, reconstructing andpresenting to a user (such as a doctor and/or technician) physiologicaldata pertaining to the heart's electrical activity may be based oninformation acquired at multiple locations, thereby providing a moreaccurate and faithful reconstruction of physiological behavior of theendocardium surface. The acquisition of signals at multiple catheterlocations in the heart chamber enables the catheter to effectively actas a “mega-catheter” whose effective number of electrodes and electrodespan is proportional to the product of the number of locations in whichsignal acquisition is performed and the number of electrodes thecatheter has.

To enhance the quality of the reconstructed physiological information atthe endocardium surface, in some embodiments the catheter 110 is movedto more than three locations (for example, more than 5, 10, or even 50locations) within the heart chamber. Further, the spatial range overwhich the catheter is moved may be larger than one third (⅓) of thediameter of the heart cavity (for example, larger than 35%, 40%, 50% oreven 60% of the diameter of the heart cavity). Additionally, in someembodiments the reconstructed physiological information is computedbased on signals measured over several heart beats, either at a singlecatheter location within the heart chamber or over several locations. Incircumstances where the reconstructed physiological information is basedon multiple measurements over several heart beats, the measurements maybe synchronized with one another so that the measurement are performedat approximately the same phase of the heart cycle. The signalmeasurements over multiple beats may be synchronized based on featuresdetected from physiological data such as surface electrocardiograms(ECGs) and/or intracardiac electrograms (EGMs).

The cardiac mapping system 100 further includes a processing unit 120which performs several of the operations pertaining to the mappingprocedure, including the reconstruction procedure to determine thephysiological information at the endocardium surface (e.g., as describedabove) and/or within a heart chamber. The processing unit 120 also mayperform a catheter registration procedure. The processing unit 120 alsomay generate a 3D grid used to aggregate the information captured by thecatheter 110 and to facilitate display of portions of that information.

The location of the catheter 110 inserted into the heart chamber can bedetermined using a conventional sensing and tracking system 180 thatprovides the 3D spatial coordinates of the catheter and/or its multipleelectrodes with respect to the catheter's coordinate system asestablished by the sensing and tracking system. These 3D spatiallocations may be used in building the 3D grid. Embodiments of the system100 may use a hybrid location technology that combines impedancelocation with magnetic location technology. This combination may enablethe system 100 to accurately track catheters that are connected to thesystem 100. Magnetic location technology uses magnetic fields generatedby a localization generator positioned under the patient table to trackcatheters with magnetic sensors. Impedance location technology may beused to track catheters that may not be equipped with a magneticlocation sensor, and may utilize surface ECG patches.

In embodiments, to perform a mapping procedure and reconstructphysiological information on the endocardium surface, the processingunit 120 may align the coordinate system of the catheter 110 with theendocardium surface's coordinate system. The processing unit 110 (orsome other processing component of the system 100) may determine acoordinate system transformation function that transforms the 3D spatialcoordinates of the catheter's locations into coordinates expressed interms of the endocardium surface's coordinate system, and/or vice-versa.In embodiments, such a transformation may not be necessary, asembodiments of the 3D grid described herein may be used to capturecontact and non-contact EGMs, and select mapping values based onstatistical distributions associated with nodes of the 3D grid. Theprocessing unit 120 also may perform post-processing operations on thephysiological information to extract and display useful features of theinformation to the operator of the system 100 and/or other persons(e.g., a physician).

According to embodiments, the signals acquired by the multipleelectrodes of catheter 110 are passed to the processing unit 120 via anelectrical module 140, which may include, for example, a signalconditioning component. The electrical module 140 may be configured toreceive the signals communicated from the catheter 110 and performsignal enhancement operations on the signals before they are forwardedto the processing unit 120. The electrical module 140 may include signalconditioning hardware, software, and/or firmware that may be used toamplify, filter and/or sample intracardiac potential measured by one ormore electrodes. The intracardiac signals typically have a maximumamplitude of 60 mV, with a mean of a few millivolts.

In some embodiments the signals are bandpass filtered in a frequencyrange (e.g., 0.5-500 Hz) and sampled with analog to digital converters(e.g., with 15-bit resolution at 1 kHz). To avoid interference withelectrical equipment in the room, the signal may be filtered to removethe frequency corresponding to the power supply (e.g., 60 Hz). Othertypes of signal processing operations such as spectral equalization,automatic gain control, etc. may also take place. For example, inembodiments, the intracardiac signals may be unipolar signals, measuredrelative to a reference (which may be a virtual reference) such as, forexample, a coronary sinus catheter or Wilson's Central Terminal (WCT),from which the signal processing operations may compute differences togenerate multipolar signals (e.g., bipolar signals, tripolar signals,etc.). The signals may be otherwise processed (e.g., filtered, sampled,etc.) before and/or after generating the multipolar signals. Theresultant processed signals are forwarded by the module 140 to theprocessing unit 120 for further processing.

In embodiments, the processing unit 120 may be configured to process theresultant processed signals. In embodiments, because the processing unit120 may be configured to process any number of different types ofelectrical signals, whether they have been preprocessed or not, theterms “electrical signal(s),” “cardiac electrical signal(s)” and termsincluding one or more of the aforementioned, shall be understood torefer to electrical signals, processed (e.g., “pre-processed”)electrical signals, raw signal data, interpolated electrical signals,estimated electrical signals, and/or any other type of informationrepresenting an electrical signal, as described herein.

Embodiments of the processing unit 120 may be configured to receive anumber of electrical signals such as, for example, cardiac electricalsignals. The processing unit 120 may receive the electrical signals fromthe electrical module 140, from a memory device, from a catheter (e.g.,the catheter 110), from another computing device, from a user via a userinput device, and/or the like. In embodiments, the processing unit 120may receive an indication of a measurement location corresponding toeach electrical signal. The processing unit 120 may be configured togenerate, based on the electrical signals, a cardiac map, which may bepresented via a display device 170. In embodiments, the cardiac mapincludes a number of annotations representing a number of cardiac signalfeatures, which may include, for example, one or more activation times,minimum voltage values, maximum voltage values, maximum negativetime-derivatives of voltage, instantaneous potentials, voltageamplitudes, dominant frequencies, and/or peak-to-peak voltages.

The processing unit 120 may be further configured to determine, from thecardiac signal features, a set of interesting cardiac signal features.According to embodiments, an “interesting” cardiac signal feature is acardiac signal feature that has been designated as such, such as, forexample, via user input, an automatic algorithm, and/or the like. Theprocessing unit 120 may also be configured to determine, based on theset of interesting cardiac signal features, a region of interest (ROI).In embodiments, an ROI refers to a set of information that is designatedas interesting, and may, in embodiments be determined based on anotherset of information designated as interesting. That is, for example, theprocessing unit 120 may be configured to determine (e.g., based on userinput, an algorithm, etc.) a set of interesting electrical signalfeatures (e.g., a set of information that is designated as interesting)and, based on the set of interesting signal features, a region ofinterest (e.g., another set of information that is designated asinteresting). In embodiments, a region of interest may refer to a set ofmapped data points such as, for example, a set of data points that aremapped, using a mesh, to an electroanatomical shell surface (e.g., acardiac model). A region of interest may include the set of interestingcardiac signal features, information associated with the set ofinteresting cardiac signal features, and/or the like.

According to embodiments, the processing unit 120 may be configured tofacilitate display, via a display device 170, of the cardiac map and arepresentation of the region of interest. The representation of theregion of interest may include, for example, a first display parametervalue that is different from a second display parameter value. Inembodiments, the display parameter may include any number of differenttypes of parameters, settings, and/or the like that may be configured tochange one or more features of an appearance of a displayedrepresentation. For example, in embodiments, display parameters mayinclude brightness, contrast, color saturation, sharpness, and/or thelike. Thus, in embodiments, the representation of the region of interestmay include a first color saturation value that is different from asecond color saturation value, where the second color saturation valueis associated with at least one cardiac signal feature that is notincluded within the region of interest. Color saturation values,relative color saturation values, and/or the like, may be adjustable viauser input, an algorithm, and/or the like.

As further shown in FIG. 1, the cardiac mapping system 100 also mayinclude peripheral devices such as a printer 150 and/or display device170, both of which may be interconnected to the processing unit 120.Additionally, the mapping system 100 includes storage device 160 thatmay be used to store data acquired by the various interconnectedmodules, including the volumetric images, raw data measured byelectrodes and/or the resultant endocardium representation computedtherefrom, the partially computed transformations used to expedite themapping procedures, the reconstructed physiological informationcorresponding to the endocardium surface, and/or the like.

In embodiments, the processing unit 120 may be configured toautomatically improve the accuracy of its algorithms by using one ormore artificial intelligence (i.e., machine-learning) techniques,classifiers, and/or the like. In embodiments, for example, theprocessing unit may use one or more supervised and/or unsupervisedtechniques such as, for example, support vector machines (SVMs),k-nearest neighbor techniques, artificial neural networks, and/or thelike. In embodiments, classifiers may be trained and/or adapted usingfeedback information from a user, other metrics, and/or the like.

The illustrative cardiac mapping system 100 shown in FIG. 1 is notintended to suggest any limitation as to the scope of use orfunctionality of embodiments of the present disclosure. Neither shouldthe illustrative cardiac mapping system 100 be interpreted as having anydependency or requirement related to any single component or combinationof components illustrated therein. Additionally, various componentsdepicted in FIG. 1 may be, in embodiments, integrated with various onesof the other components depicted therein (and/or components notillustrated), all of which are considered to be within the ambit of thesubject matter disclosed herein. For example, the electrical module 140may be integrated with the processing unit 120. Additionally, oralternatively, aspects of embodiments of the cardiac mapping system 100may be implemented in a computer analysis system configured to receivecardiac electrical signals and/or other information from a memory device(e.g., a cloud server, a mapping system memory, etc.), and performaspects of embodiments of the methods described herein for processingcardiac information (e.g., determining annotation waveforms, etc.). Thatis, for example, a computer analysis system may include a processingunit 120, but not a mapping catheter.

FIG. 2 is a block diagram of an illustrative processing unit 200, inaccordance with embodiments of the disclosure. The processing unit 200may be, be similar to, include, or be included in the processing unit120 depicted in FIG. 1. As shown in FIG. 2, the processing unit 200 maybe implemented on a computing device that includes a processor 202 and amemory 204. Although the processing unit 200 is referred to herein inthe singular, the processing unit 200 may be implemented in multipleinstances (e.g., as a server cluster), distributed across multiplecomputing devices, instantiated within multiple virtual machines, and/orthe like. One or more components for facilitating cardiac mapping may bestored in the memory 204. In embodiments, the processor 202 may beconfigured to instantiate the one or more components to generate one ormore electrical signal features 206 and a cardiac map 208, either ofwhich may be stored in the memory 204.

As is further depicted in FIG. 2, the processing unit 200 may include anacceptor 210 configured to receive electrical signals. The acceptor 210may be configured to receive electrical signals from a mapping catheter(e.g., the mapping catheter 110 depicted in FIG. 1), a memory device(e.g., the memory 204), a server, and/or the like. The measuredelectrical signals may include a number of intracardiac electrograms(EGMs) sensed within a patient's heart. The acceptor 210 may alsoreceive an indication of a measurement location corresponding to each ofthe electrical signals. In embodiments, the acceptor 210 may beconfigured to determine whether to accept the electrical signals thathave been received. The acceptor 210 may utilize any number of differentcomponents and/or techniques to determine which electrical signals orbeats to accept, such as filtering, beat matching, morphology analysis,positional information (e.g., catheter motion), respiration gating,and/or the like.

The accepted electrical signals are received by a feature extractor 212that is configured to extract at least one electrical signal featurefrom each of the electrical signals. In embodiments, an extractedelectrical signal feature may be used to annotate a cardiac map, inwhich case, the extracted electrical signal feature may be referred to,interchangeably, as an annotation feature. In embodiments in which theelectrical signal is a cardiac electrical signal, an extracted signalfeature may be referred to, interchangeably, as a cardiac electricalsignal feature. In embodiments, the at least one electrical signalfeature includes at least one value corresponding to at least oneannotation metric. The at least one feature may include at least oneevent, where the at least one event includes the at least one valuecorresponding to the at least one metric and/or at least onecorresponding time (a corresponding time does not necessarily exist foreach annotation feature). According to embodiments, the at least oneelectrical signal feature may include, for example, an activation time,detected activation (e.g., a component of an activation waveform),activation waveform, activation histogram, minimum voltage value,maximum voltage value, maximum negative time-derivative of voltage, aninstantaneous potential, a voltage amplitude, a dominant frequency, apeak-to-peak voltage, an activation duration, an annotation waveform(e.g., an activation waveform), and/or the like. A cardiac electricalsignal feature may refer to one or more features extracted from one ormore cardiac electrical signals, derived from one or more features thatare extracted from one or more cardiac electrical signals, and/or thelike. Additionally, a representation, on a cardiac and/or a surface map,of a cardiac electrical signal feature may represent one or more cardiacelectrical signal features, an interpolation of a number of cardiacelectrical signal features, and/or the like.

According to embodiments, feature extractor 212 may be configured todetect specified events (e.g., activations) and to generate anannotation waveform (a type of electrical signal feature 206), which maybe, for example, an activation waveform. An annotation waveform is a setof annotation waveform values and may include, for example, a set ofdiscrete activation annotation values (e.g., a set of annotationwaveform values, a set of time annotations, etc.), a function definingan annotation waveform curve, and/or the like. Accordingly, inembodiments, the term “annotation waveform” may include a “filteredannotation waveform.” An activation waveform is a set of activationwaveform values and may include, for example, a set of discreteactivation waveform values (e.g., a set of activation waveform values, aset of activation time annotations, etc.), a function defining anactivation waveform curve, and/or the like. Accordingly, in embodiments,the term “activation waveform” may include a “filtered activationwaveform.”

According to embodiments, the feature extractor 212 may be, include, besimilar to, or be included in, aspects of embodiments of the annotationwaveform generator described in U.S. Application No. 62/486,926, filedon Apr. 18, 2017, entitled “ANNOTATION WAVEFORM;” U.S. Application No.62/486,909, filed on Apr. 18, 2017, entitled “ELECTROANATOMICAL MAPPINGTOOLS FACILITATED BY ACTIVATION WAVEFORMS;” and/or U.S. Application No.62/486,920, filed on Apr. 18, 2017, entitled “ANNOTATION HISTOGRAM;” theentirety of each of which is hereby incorporated by reference herein forall purposes. In embodiments, the feature extractor 212 may beconfigured to generate an annotation histogram (another type ofelectrical signal feature 206) having a number of bins within whichannotations from electrograms (EGMs) are included. The feature extractor212 may be configured to aggregate a set of annotation features byincluding each of the features and/or EGMs in a histogram. For example,the feature extractor 212 may be configured to aggregate the set ofactivation features by assigning a confidence level to each eventcorresponding to an activation feature; determining a weightedconfidence level associated with each event; and including the weightedconfidence levels in a histogram. According to embodiments, the featureextractor 212 may be, include, be similar to, or be included in, aspectsof embodiments of the histogram generator described in U.S. ApplicationNo. 62/486,926, filed on Apr. 18, 2017, entitled “ANNOTATION WAVEFORM;”U.S. Application No. 62/486,909, filed on Apr. 18, 2017, entitled“ELECTROANATOMICAL MAPPING TOOLS FACILITATED BY ACTIVATION WAVEFORMS;”and/or U.S. Application No. 62/486,920, filed on Apr. 18, 2017, entitled“ANNOTATION HISTOGRAM;” incorporated above.

As shown in FIG. 2, the processing unit 200 includes a region ofinterest (ROI) component 214. According to embodiments, the ROIcomponent 214 is configured to determine a set of interesting cardiacsignal features. According to embodiments, an “interesting” cardiacsignal feature is a cardiac signal feature that has been designated assuch, such as, for example, via user input, an automatic algorithm,and/or the like. In embodiments, for example, in embodiments, a user(e.g., a clinician) interacts with a graphical user interface (GUI) viaa user input device to select a set of interesting cardiac signalfeatures. In embodiments, the GUI may facilitate selection of one ormore cardiac signal features, cardiac signal feature ranges, and/or thelike, via interaction with a GUI. For example, in embodiments, a the GUImay include interactive representations of sliders, buttons, knobs,and/or the like, that enable user selection of various electrical signalfeatures, device parameters, physiological parameters, environmentalparameters, and/or the like. In embodiments, the GUI may allow the userto interact with the cardiac map directly (e.g., by utilizing a cursorto select points and/or regions of the map, hover over points and/orregions of the map, etc.) to facilitate identification of a set ofinteresting electrical signal features (and, thus, a region ofinterest). The processing unit 200 may be configured to determine a setof interesting electrical signal features based on the user interactionwith the GUI.

In embodiments, the processing unit 200 may be configured toautomatically determine a set of interesting electrical signal featuressuch as, for example, by classifying electrical signal features asinteresting based on one or more classification criteria. Inembodiments, the classification criteria may be user selectable and/oradjustable. In embodiments, the criteria may be automatically selectedand/or adjusted by the processing unit 200 in response to an indirectlyrelated user input (e.g., a user input that facilitates display and/oradjustment of corresponding annotations. In embodiments, the set ofinteresting electrical signal features may be determinedprogrammatically, to facilitate any number of different types of mapfunctionality.

According to embodiments, the ROI component 214 may be configured todetermine, based on the set of interesting cardiac signal features, anROI. In embodiments, for example, the ROI includes the set ofinteresting cardiac signal features and/or the mapped informationcorresponding thereto. In embodiments, for example, the ROI component214 may be configured to determine, for each cardiac signal feature ofthe set of cardiac signal features, a radius of influence. A radius ofinfluence of an electrical signal feature is a metric (e.g., a scalarvalue, a vector, a combination of scalar values and/or vectors, etc.)that represents a spatial region within which the electrical signalfeature has an effect and/or is likely to have an effect. For example,in embodiments, the radius of influence of a cardiac electrical signalfeature may be a distance along the surface of the anatomical shell(e.g., a cardiac model) for which the cardiac signal feature hasphysiological significance—that is, for example, the radius of influenceof a feature may correspond to a portion of the surface of the cardiacmap that is annotated based at least in part on the feature.

In embodiments, the ROI component 214 may determine the radius ofinfluence of an electrical signal feature in any number of ways such as,for example, to obtain (e.g. from a mapping engine) an indication of theportion of the cardiac map that was annotated at least partially basedon the electrical signal feature. In embodiments, the ROI component 214may determine the radius of influence of an electrical signal feature bydetermining a likelihood (e.g., probability) that the electrical signalfeature (and/or other electrical signal features associated with thecorresponding electrical signal) would have an influence (e.g., bycontributing to a portion of operation of the heart, by contributing toan arrhythmia, by contributing to a signal measured within a certaindistance, and/or the like. In embodiments, the radius of influence mayrefer to a surface distance (e.g., a cumulative distance along thecontour of the surface of the map, rather than a Euclidean distance suchas, e.g., the length of the radius of an imaginary sphere around thepoint) of a map.

According to embodiments, the ROI component 214 may be configured todetermine the region of interest based on the determined radius ofinfluence for each cardiac signal feature. That is, for example, the ROIcomponent 214 may connect the map portions corresponding to theelectrical signal features of the set of interesting electrical signalfeatures to form the ROI. In embodiments, the ROI may be a continuoustwo-dimensional portion of the map, multiple disconnectedtwo-dimensional portions of the map, and/or the like. In embodiments, analgorithm (e.g., aspects of embodiments of the methods described hereinfor vertex-based highlight generation, pixel-based highlight generation,etc.) may be configured to connect highlighted map portions (e.g., mapportions corresponding to radii of influence) to form larger regions(e.g., ROIs, portions of ROIs, etc.). The algorithm may be configured todetermine whether to connect the larger portions, which portionscorresponding to radii of influence to connect, and/or the like. Inembodiments, the ROI component 214 may be configured to performinterpolation such that, for example, two areas that are within somespecified distance of one another may be connected (e.g., assuming oneor more criteria are satisfied such as, e.g., there are no uninterestingpoints—data points that are to be left unhighlighted—between the tworegions).

Additionally, the processing unit 200 includes a mapping engine 216 thatis configured to facilitate presentation of a map 208 corresponding to acardiac surface based on the electrical signals. In embodiments, the map208 may include a voltage map, an activation map, a fractionation map,velocity map, confidence map, and/or the like. In embodiments, themapping engine 216 may be, include, be similar to, be included within,and/or be otherwise integrated with the ROI component 214. Inembodiments, the mapping engine 216 may be configured to facilitatedisplay, via the display device, of the cardiac map and a representationof the region of interest. As shown, for example, a representation of aregion of interest may include a first color saturation value that isdifferent from a second color saturation value, where the second colorsaturation value is associated with at least one cardiac signal featurethat is not included within the region of interest. In embodiments, morethan one representation of a region of interest may be presented on themap.

In embodiments, a representation of a region of interest is presented asa highlighted area of a map. Mesh pixels (pixels associated with a meshthat is used to generate the map) within the highlighted regions mayappear to have a lighting effect that distinguishes them from the meshpixels that are not within the highlighted regions, while preserving allof the information presented on the map (e.g., the annotation colors,hues, brightness, and other attributes associated with a region ofinterest are preserved when the region is highlighted because only therelative saturation level is adjusted—e.g., as opposed to dimming themap, adjusting transparency, etc.). In embodiments, to present therepresentation of a region of interest, portions of the map that are notwithin the region of interest may be de-saturated (e.g., displayed witha lower saturation value than the saturation value with which thoseareas were displayed prior to presenting the representation), whileportions of the map within the region of interest may be oversaturatedor at least displayed with a saturation value that exceeds thesaturation value with which the regions were displayed prior topresenting the representation of the region of interest. In embodiments,an amount of saturation of a highlighted area is greater than the amountof saturation of a non-highlighted area. According to embodiments, thesaturation of highlighted areas and/or non-highlighted areas may beselected, controlled, and/or otherwise influenced (e.g., controlledwithin certain allowed parameters) by a user. An illustrativehighlighting operation is depicted in FIGS. 3A & 3B.

FIG. 3A depicts an illustrative screenshot from an interactive graphicaluser interface (GUI) presented using a display device associated with acardiac mapping system, showing an illustrative cardiac map 300, inaccordance with embodiments of the subject matter disclosed herein.According to embodiments, the cardiac mapping system may be, be similarto, include similar features as, include, or be included within themapping system 100 depicted in FIG. 1. In embodiments, the GUI may beconfigured to present only one view of the cardiac map 300 at a time. Inembodiments, the GUI may be configured to present, simultaneously,sequentially, and/or alternatively, any number of different views of anynumber of cardiac maps. In embodiments, for example, the GUI may beconfigured to present a first cardiac map having annotationsrepresenting activations and a second cardiac map having annotationsrepresenting electrical potential, current density, and/or the like.

As shown in FIG. 3A, the cardiac map 300 includes an anatomical shell302 and annotations 304 displayed on the anatomical shell 302. Inembodiments, the map may be an activation map, on which activationlocations are indicated by raised bumps 306. In embodiments, raisedbumps 306 (or other displayed features) may be used to indicate anynumber of different metrics, values, events, and/or the like. Inembodiments, annotations (e.g., electrical signal features, quantitiescorresponding to—e.g., derived from—electrical signal features) may berepresented using colors 308, 310, 312, 314, 316, and 318. Although sixdistinct colors are discussed herein, any number of colors may be usedfor such representations. In embodiments, in addition to, or in lieu of,colors, other representations may be used to represent activations suchas, for example, textures, location markers, curves, vectors, and/or thelike. In embodiments, the raised bumps 306 may be configured torepresent a location associated with an acquired electrical signal(e.g., an EGM), a virtual location associated with an aggregation ofacquired electrical signals, and/or the like. In embodiments, the GUImay also include a legend (not shown) configured to indicate the valuesrepresented by the annotation colors 308, 310, 312, 314, 316, and 318.

Embodiments facilitate presenting, on a cardiac map, a representation ofa region of interest (ROI) by highlighting a corresponding portion ofthe cardiac map. FIG. 3B an illustrative screenshot from an interactiveGUI, showing another view of the cardiac map 300 depicted in FIG. 3A, inaccordance with embodiments of the subject matter disclosed herein.According to embodiments, the cardiac map 300 may be, or include, one ormore selectable GUI elements such that, for example, a user can move acursor over a portion of the cardiac map 300 and select the portion ofthe cardiac map 300 to which the cursor points, for example, by pressinga mouse button, tapping a touchscreen, and/or the like.

According to embodiments, for example, the GUI may be configured toreceive, from a user input device, a selection of a region of thecardiac map 300. The user input device used to make the selection mayinclude a mouse, a touchscreen and/or the like, that is used tomanipulate a selection tool that is provided on the GUI provided by thedisplay device. The selection tool may include, for example, a brush, acursor for enclosing the selected region by drawing a freeform shapearound the region, an expandable polygon selection tool, a virtualprobe, and/or the like, and may be, in embodiments, selected from anumber of optional selection tools. In embodiments, the selection toolmay have an adjustable size, behavior and/or other characteristicsthereof. In this manner, for example, a user may select a desiredselection tool and a size thereof. Selecting a region of the map 300 mayinclude, for example, circling the region of the map using a mouse ortouchscreen device to manipulate a cursor, brushing over the region ofthe map using an input device to manipulate a brush, and/or the like.According to embodiments, one or more portions of a map may beinteractive such that a user may position a mouse cursor over a portionof the map, and interact with that portion (e.g., by clicking a rightmouse button) to reveal additional information and/or functionality.

In embodiments, in response to receiving an indication of the userselection of a portion of the cardiac map 300, the processing unit maycause a corresponding region (referred to herein as the “selectedregion”) of the map 300 to be highlighted. Similarly, the GUI mayinclude one or more selectable elements separate from the cardiac map300 (e.g., selectable waveforms, histograms, EGMs, parameters, etc.)that may be selected using a user input device to cause the processingunit to highlight a corresponding portion 320 of the map 300. Inembodiments, information corresponding to the user selection may be,include, or be included in a region of interest (ROI), and thehighlighted portion 320 of the map 300 may be, include, or be includedin a representation of the ROI.

According to embodiments, for example, a user may interact with a mouse,and may manipulate the mouse to move a mouse cursor over a portion ofthe map. When the user presses and holds a mouse button, the processingunit may determine a ray extending from the location of the point of themouse cursor to the mesh, e.g., in a direction that is normal to themesh (or in a direction associated with movement of the mouse cursor,etc.). The processing unit may be configured to determine a location(e.g., a mesh element) at which the ray intersects the mesh, and may beconfigured to determine one or more pixels associated with the meshelement. The one or more pixels may be highlighted as a representationof a region of interest (ROI). In embodiments, the user may expand theregion of interest by moving the mouse cursor, while holding down themouse button, causing the process to additively generate a larger ROI.

The representation 320 of the ROI may be configured to emphasize theportion of the map 300 corresponding to the ROI. In embodiments, forexample, the representation 320 of ROI may be distinguished fromadjacent regions of the map 300 by being highlighted. That is, forexample, the representation 320 of the ROI may be a highlighting of thecorresponding portion of the map (e.g., by presenting therepresentations of the electrical signal features in the representation320 using a color saturation different than the color saturation ofother portions of the map 300). In embodiments, as shown in FIG. 3B, therepresentation 320 of the ROI may include a border 322 outlining theregion. The border 322 may presented in a color that is different thanone or more of the colors used to annotate the map 300 (e.g., a colordifferent than any color used in any pixel or group of pixels of acertain size disposed adjacent the border). For example, in embodiments,the border 322 may be white. The border 322 may be configured to helpdelineate the representation 320 of the ROI, create the feel of adiscrete region, and/or assist in situations where some display devicesand/or lighting conditions make the highlighting itself more difficultfor a user to see. In embodiments, individual electrical signal featuresand/or locations may be indicated using representations 324 such as“Xs,” raised bumps, and/or the like.

The illustrative processing unit 200 shown in FIG. 2 and theillustrative cardiac maps 300 are not intended to suggest any limitationas to the scope of use or functionality of embodiments of the presentdisclosure. Neither should the illustrative processing unit 200 and/orthe cardiac map 500 be interpreted as having any dependency orrequirement related to any single component or combination of componentsillustrated therein. Additionally, any one or more of the componentsand/or features depicted in FIGS. 2, 3A, and 3B may be, in embodiments,integrated with various ones of the other components and/or featuresdepicted therein (and/or components not illustrated), all of which areconsidered to be within the ambit of the subject matter disclosedherein. For example, the acceptor 210 may be integrated with the featureextractor 212, the ROI component 214, and/or the mapping engine 216. Inembodiments, the processing unit 200 may not include an acceptor 210,while in other embodiments, the acceptor 210 may be configured toreceive electrical signals from a memory device, a communicationcomponent, and/or the like.

Additionally, the processing unit 200 may (alone and/or in combinationwith other components of the system 100 depicted in FIG. 1, and/or othercomponents not illustrated) perform any number of different functionsand/or processes associated with cardiac mapping (e.g., triggering,blanking, field mapping, etc.) such as, for example, those described inU.S. Pat. No. 8,428,700, entitled “ELECTROANATOMICAL MAPPING;” U.S. Pat.No. 8,948,837, entitled “ELECTROANATOMICAL MAPPING;” U.S. Pat. No.8,615,287, entitled “CATHETER TRACKING AND ENDOCARDIUM REPRESENTATIONGENERATION;” U.S. Patent Publication 2015/0065836, entitled “ESTIMATINGTHE PREVALENCE OF ACTIVATION PATTERNS IN DATA SEGMENTS DURINGELECTROPHYSIOLOGY MAPPING;” U.S. Pat. No. 6,070,094, entitled “SYSTEMSAND METHODS FOR GUIDING MOVABLE ELECTRODE ELEMENTS WITHINMULTIPLE-ELECTRODE STRUCTURE;” U.S. Pat. No. 6,233,491, entitled“CARDIAC MAPPING AND ABLATION SYSTEMS;” U.S. Pat. No. 6,735,465,entitled “SYSTEMS AND PROCESSES FOR REFINING A REGISTERED MAP OF A BODYCAVITY;” the disclosures of which are hereby expressly incorporatedherein by reference.

According to embodiments, various components of the mapping system 100,illustrated in FIG. 1, and/or the processing unit 200, illustrated inFIG. 2, may be implemented on one or more computing devices. A computingdevice may include any type of computing device suitable forimplementing embodiments of the disclosure. Examples of computingdevices include specialized computing devices or general-purposecomputing devices such “workstations,” “servers,” “laptops,” “desktops,”“tablet computers,” “hand-held devices,” “general-purpose graphicsprocessing units (GPGPUs),” and the like, all of which are contemplatedwithin the scope of FIGS. 1 and 2 with reference to various componentsof the system 100 and/or processing unit 200.

In embodiments, a computing device includes a bus that, directly and/orindirectly, couples the following devices: a processor, a memory, aninput/output (I/O) port, an I/O component, and a power supply. Anynumber of additional components, different components, and/orcombinations of components may also be included in the computing device.The bus represents what may be one or more busses (such as, for example,an address bus, data bus, or combination thereof). Similarly, inembodiments, the computing device may include a number of processors, anumber of memory components, a number of I/O ports, a number of I/Ocomponents, and/or a number of power supplies. Additionally any numberof these components, or combinations thereof, may be distributed and/orduplicated across a number of computing devices.

In embodiments, memory (e.g., the storage device 160 depicted in FIG. 1,and/or the memory 204 depicted in FIG. 2) includes computer-readablemedia in the form of volatile and/or nonvolatile memory and may beremovable, nonremovable, or a combination thereof. Media examplesinclude Random Access Memory (RAM); Read Only Memory (ROM);Electronically Erasable Programmable Read Only Memory (EEPROM); flashmemory; optical or holographic media; magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices; datatransmissions; and/or any other medium that can be used to storeinformation and can be accessed by a computing device such as, forexample, quantum state memory, and/or the like. In embodiments, thememory 160 and/or 204 stores computer-executable instructions forcausing a processor (e.g., the processing unit 120 depicted in FIG. 1and/or the processor 202 depicted in FIG. 2) to implement aspects ofembodiments of system components discussed herein and/or to performaspects of embodiments of methods and procedures discussed herein.

Computer-executable instructions may include, for example, computercode, machine-useable instructions, and the like such as, for example,program components capable of being executed by one or more processorsassociated with a computing device. Examples of such program componentsinclude the electrical signal feature 206, the map 208, the acceptor210, the feature extractor 212, the ROI component 214, and/or themapping engine 216. Program components may be programmed using anynumber of different programming environments, including variouslanguages, development kits, frameworks, and/or the like. Some or all ofthe functionality contemplated herein may also, or alternatively, beimplemented in hardware and/or firmware.

FIG. 4 is a flow diagram of an illustrative process 400 for automatedelectro-anatomical mapping, in accordance with embodiments of thedisclosure. Aspects of embodiments of the method 400 may be performed,for example, by a processing unit (e.g., the processing unit 120depicted in FIG. 1, and/or the processing unit 200 depicted in FIG. 2).A data stream 402 containing multiple signals is first input into thesystem (e.g., the cardiac mapping system 100 depicted in FIG. 1). Duringthe automated electro-anatomical mapping process, a data stream 402provides a collection of physiological and non-physiological signalsthat serve as inputs to the mapping process. The signals may becollected directly by the mapping system, and/or obtained from anothersystem using an analog or digital interface. The data stream 402 mayinclude signals such as unipolar and/or bipolar intracardiacelectrograms (EGMs), surface electrocardiograms (ECGs), electrodelocation information originating from one or more of a variety ofmethodologies (magnetic, impedance, ultrasound, real time MRI, etc.),tissue proximity information, catheter force and/or contact informationobtained from one or more of a variety of methodologies (force springsensing, piezo-electric sensing, optical sensing etc.), catheter tipand/or tissue temperature, acoustic information, catheter electricalcoupling information, catheter deployment shape information, electrodeproperties, respiration phase, blood pressure, other physiologicalinformation, and/or the like.

For the generation of specific types of maps, one or more signals may beused as one or more references, during a triggering/alignment process404, to trigger and align the data stream 402 relative to the cardiac,other biological cycle and/or an asynchronous system clock resulting inbeat datasets. Additionally, for each incoming beat dataset, a number ofbeat metrics are computed during a beat metric determination process406. Beat metrics may be computed using information from a singlesignal, spanning multiple signals within the same beat and/or fromsignals spanning multiple beats. The beat metrics provide multiple typesof information on the quality of the specific beat dataset and/orlikelihood that the beat data is good for inclusion in the map dataset.A beat acceptance process 408 aggregates the criteria and determineswhich beat datasets will make up the map dataset 410. The map dataset410 may be stored in association with a 3D grid that is dynamicallygenerated during data acquisition.

Surface geometry data may be generated concurrently during the same dataacquisition process using identical and/or different triggering and/orbeat acceptance metrics employing a surface geometry constructionprocess 412. This process constructs surface geometry using data such aselectrode locations and catheter shape contained in the data stream.Additionally, or alternatively, previously collected surface geometry416 may be used as an input to surface geometry data 418. Such geometrymay have been collected previously in the same procedure using adifferent map dataset, and/or using a different modality such as CT,MRI, ultrasound, rotational angiography, and/or the like, and registeredto the catheter locating system. The system performs a source selectionprocess 414, in which it selects the source of the surface geometry dataand provides surface geometry data 418 to a surface map generationprocess 420. The surface map generation process 420 is employed togenerate surface map data 422 from the map dataset 410 and surfacegeometry data 418.

The surface geometry construction algorithm generates the anatomicalsurface on which the electroanatomical map is displayed. Surfacegeometry can be constructed, for example, using aspects of a system asdescribed U.S. patent application Ser. No. 12/437,794, entitled“Impedance Based Anatomy Generation” and filed on May 8, 2008; and/orU.S. Pat. No. 8,948,837, entitled “Electroanatomical Mapping” and issuedon Feb. 3, 2015, the contents of each of which is incorporated byreference herein in its entirety. Additionally, or alternatively, ananatomical shell can be constructed by the processing unit by fitting asurface on electrode locations that are determined either by the user orautomatically to be on the surface of the chamber. In addition, asurface can be fit on the outermost electrode and/or catheter locationswithin the chamber.

As described, the map dataset 410 from which the surface is constructedcan employ identical or different beat acceptance criteria from thoseused for electrical and other types of maps. The map dataset 410 forsurface geometry construction can be collected concurrently withelectrical data or separately. Surface geometry can be represented as amesh containing a collection of vertices (points) and the connectivitybetween them (e.g. triangles). Alternatively, surface geometry can berepresented by different functions such as higher order meshes,non-uniform rational basis splines (NURBS), and/or curvilinear shapes.

The generation process 420 generates surface map data 422. The surfacemap data 422 may provide information on cardiac electrical excitation,cardiac motion, tissue proximity information, tissue impedanceinformation, force information, and/or any other collected informationdesirable to the clinician. The combination of map dataset 410 andsurface geometry data 418 allows for surface map generation. The surfacemap is a collection of values or waveforms (e.g., EGMs) on the surfaceof the chamber of interest, whereas the map dataset can contain datathat is not on the cardiac surface. One approach for processing the mapdataset 410 and surface geometry data 418 to obtain a surface mapdataset 422 is described in U.S. Pat. No. 7,515,954, entitled“NON-CONTACT CARDIAC MAPPING, INCLUDING MOVING CATHETER AND MULTI-BEATINTEGRATION” and filed Jun. 13, 2006, the contents of which isincorporated by reference herein in its entirety.

Alternatively, or in combination with the method above, an algorithmthat applies acceptance criteria to individual electrodes can beemployed. For example, electrode locations exceeding a set distance(e.g., 3 mm) from surface geometry can be rejected. Another algorithmcan incorporate tissue proximity information using impedance forinclusion in the surface map data. In this case only electrode locationwhose proximity value is less than 3 mm might be included. Additionalmetrics of the underlying data can also be used for this purpose. Forexample, EGM properties similar to beat metrics can be assessed on a perelectrode basis. In this case metrics such as far field overlap and/orEGM consistency can be used. It should be understood that variations onthe method to project points from the map dataset 410 to the surfaceand/or to select appropriate points can exist.

Once obtained, the surface map data 422 may be further processed toannotate desired features from the underlying data, a process defined assurface map annotation 424. Once data is collected into surface map data422, attributes relating to the collected data may be automaticallypresented to the user. These attributes can be automatically determinedand applied to the data by the computer system and are referred toherein as annotations. Exemplary annotations include activation time,the presence of double activation or fractionation, voltage amplitude,spectral content, and/or the like. Due to the abundance of dataavailable in automated mapping (e.g., mapping completed by the computersystem with minimal human input related to the incoming data), it is notpractical for the operator to review and annotate data manually.However, human input can be a valuable addition to the data, and so whenuser input is provided it is necessary for the computer system toautomatically propagate and apply it to more than one data point at atime.

It may be possible to use the computer system to automatically annotateactivation time, voltage, and other characteristics of individual EGMs.Activation time detection may use methods similar to those previouslydescribed to detect a trigger and can similarly benefit from the use ofblanking and powered triggering operator. Desired annotations mayinclude instantaneous potential, activation time, voltage amplitude,dominant frequency and/or other properties of the signal. Once computed,the annotations may be displayed superimposed on chamber geometry. Inembodiments, a gap-filling surface map interpolation may be employed426. For example, in embodiments, a gap-filling interpolation may beemployed where a distance between a point on the surface to a measuredEGM exceeds a threshold, as this may indicate, for example, thatgrid-based interpolation, as described herein, may not be as effectivein that situation. Displayed maps 428 can be computed and displayedseparately, and/or overlaid on top of each other.

The illustrative method 400 shown in FIG. 4 is not intended to suggestany limitation as to the scope of use or functionality of embodiments ofthe present disclosure. Neither should the illustrative method 400 beinterpreted as having any dependency nor requirement related to anysingle aspect or combination of aspects illustrated therein.Additionally, any one or more of the aspects depicted in FIG. 4 may be,in embodiments, integrated with various ones of the other aspectsdepicted therein (and/or components not illustrated), all of which areconsidered to be within the ambit of the present disclosure.

FIG. 5 is a flow diagram depicting an illustrative method 500 ofprocessing electrophysiological information, in accordance withembodiments of the disclosure. Aspects of embodiments of the method 500may be performed, for example, by a processing unit (e.g., theprocessing unit 120 depicted in FIG. 1, and/or the processing unit 200depicted in FIG. 2). Embodiments of the method 500 include receiving aplurality of electrical signals (block 402). The electrical signals maybe received from a catheter, a memory device, a computing device, and/orthe like. The catheter may be any catheter having one or more electrodesconfigured to obtain electrical signals (e.g., the mapping catheter 110depicted in FIG. 1, a CS catheter, an ablation catheter, etc.). Theprocessing unit also may receive an indication of a measurement locationcorresponding to each of the electrical signals. As explained above,with respect to FIG. 4, the processing unit and/or other components(e.g., the electrical module 140 depicted in FIG. 1) may be configuredto determine whether to accept particular electrical signals (e.g.,beats) based on one or more beat acceptance criteria.

According to embodiments, cardiac electric signal features may beextracted from the cardiac electrical signals (e.g., EGMs). Examples offeatures of the cardiac electrical signals include, but are not limitedto, activation times, minimum voltage values, maximum voltages values,maximum negative time-derivatives of voltages, instantaneous potentials,voltage amplitudes, dominant frequencies, peak-to-peak voltages, and/orthe like. Each of the respective points at which a cardiac electricalsignal is sensed may have a corresponding set of three-dimensionalposition coordinates. For example, the position coordinates of thepoints may be represented in Cartesian coordinates. Other coordinatesystems can be used, as well. In embodiments, an arbitrary origin isused and the respective position coordinates are defined with respect tothe arbitrary origin. In some embodiments, the points have non-uniformspacing, while in other embodiments, the points have uniform spacing. Inembodiments, the point corresponding to each sensed cardiac electricalsignal may be located on the endocardial surface of the heart and/orbelow the endocardial surface of the heart.

As shown in FIG. 5, embodiments of the method 500 include determining aset of interesting cardiac electrical signal features (block 504). Theset of interesting cardiac electrical signal features may be determined,e.g., via user input and/or an automatic algorithm. Embodiments of themethod 500 include determining a radius of influence corresponding toeach cardiac electrical signal feature of the set of interesting cardiacelectrical signal features (block 506); and determining a region ofinterest (ROI) based on the set of interesting cardiac electricalsignals and the corresponding radii of influence (block 508).Embodiments of the method 500 further include facilitating presentationof an electroanatomical map on a display device (block 510) andfacilitating presentation, on the map, of a representation of the ROI(block 512).

In embodiments, a cardiac map may be generated and/or annotated based,at least in part, on the cardiac electrical signal features and/or theactivation waveform (which may also be a cardiac electrical signalfeature). In embodiments, the cardiac map may also be generated and/orannotated, at least in part, using any number of other signals,techniques, and/or the like. For example, embodiments may utilizeimpedance mapping techniques to generate and/or annotate one or moreportions of the cardiac map such as, for example, an anatomical shellupon which electrical signal features are represented. In embodiments, asurface may be fitted on one or more of the points associated with thecardiac electrical signals to generate a shell representing theendocardial surface of the one or more cardiac structures. Inembodiments, a surface may also be fitted on one or more of the pointsassociated with the cardiac electrical signals to generate a shellrepresenting an epicardium surface or other excitable cardiac tissue. Inembodiments, one or more of the cardiac electrical signal features atthe corresponding points can be included on the shell to generate acardiac map of the one or more cardiac structures. For example,embodiments may include displaying annotations on the cardiac map thatrepresent features, extracted from the cardiac electrical signals and/orderived from other features, such as, for example, activation times,minimum voltage values, maximum voltages values, maximum negativetime-derivatives of voltages, instantaneous potentials, voltageamplitudes, dominant frequencies, peak-to-peak voltages, and/or thelike.

Cardiac electrical signal features may be represented on the cardiac mapand may be, or include, any features extracted from one or morecorresponding sensed cardiac electrical signals and/or derived from oneor more of such features. For example, a cardiac electrical signalfeature may be represented by a color, such that if the cardiacelectrical signal feature has an amplitude or other value within a firstrange then the cardiac electrical signal feature may be represented by afirst color, whereas if the cardiac electrical signal feature has anamplitude or other value that is within a second range that is differentthan the first range, the cardiac electrical may be represented by asecond color. As another example, the cardiac electrical signal featuremay be represented by a number (e.g., a 0.2 mV sensed cardiac electricalsignal feature can be represented by a 0.2 at its respective position onthe surface map). Examples of a cardiac electrical signal feature thatcan be represented at the first surface point include, but are notlimited to, an activation, an activation time, an activation duration,an activation waveform, a filtered activation waveform, an activationwaveform characteristic, a filtered activation waveform characteristic,a minimum voltage value, a maximum voltages value, a maximum negativetime-derivative of voltage, an instantaneous potential, a voltageamplitude, a dominant frequency, a peak-to-peak voltage, and/or thelike.

In embodiments, other features such as, for example, non-electricalsignal features, non-cardiac electrical signal features, and/or thelike, can be represented on an anatomical map at respective locations.Examples of non-electrical signal features include, but are not limitedto, features derived from magnetic resonance imaging, a computerizedtomography scan, ultrasonic imaging, and/or the like.

According to embodiments, a GUI used for presenting the map may includeany number of different input tools for manipulating the map. Forexample, the GUI may include a play/pause button, a tool configured tofacilitate manual selection of the histogram bin or bins, toolsconfigured to facilitate manual adjustment of parameters (e.g., signalbaseline definitions, thresholds, EGM characteristics, filters, etc.),and/or the like. In embodiments, for example, the GUI may include aselection tool that can facilitate refining selections of highlightedEGMs, select particular EGMs and/or activations, and/or the like.

The illustrative method 500 shown in FIG. 5 is not intended to suggestany limitation as to the scope of use or functionality of embodiments ofthe present disclosure. Neither should the illustrative method 500 beinterpreted as having any dependency nor requirement related to anysingle aspect or combination of aspects illustrated therein.Additionally, any one or more of the aspects depicted in FIG. 5 may be,in embodiments, integrated with various ones of the other aspectsdepicted therein (and/or components not illustrated), all of which areconsidered to be within the ambit of the present disclosure.

FIG. 6 is a flow diagram depicting an illustrative method 600 offacilitating presentation of cardiac information, in accordance withembodiments of the subject matter disclosed herein. Aspects ofembodiments of the method 600 may be performed, for example, by aprocessing unit (e.g., the processing unit 120 depicted in FIG. 1,and/or the processing unit 200 depicted in FIG. 2). FIG. 7 is aconceptual schematic diagram depicting an illustrative ROI highlightingoperation, as described in embodiments of the method 600 depicted inFIG. 6, in accordance with embodiments of the subject matter disclosedherein. Embodiments of the method 600 include determining, from aplurality of cardiac electrical signal features extracted from aplurality of cardiac electrical signals, a set of interesting cardiacelectrical signal features (block 602); and determining a radius ofinfluence of each interesting cardiac electrical signal feature (block604).

As shown in FIG. 6, embodiments of the method 600 further includelabeling each mesh vertex of a mesh element of a mesh with a first value(block 606), and labeling (which may include, e.g., re-labeling) eachmesh vertex of the mesh element of the mesh with a second value if acriterion is satisfied (block 608). In embodiments, the method 600includes facilitating display of the representation of the region ofinterest based on the mesh vertex labels. That is, for example, inembodiments, as shown in FIG. 7, a triangular mesh 700 may be used forgenerating a cardiac map, and the first value may be 0, while the secondvalue is 1. In embodiments, for example, all vertices of the mesh 700may be initially labeled with a 0. For each cardiac electrical featurein the set of interesting cardiac electrical features, each vertexwithin the feature's radius of influence may be labeled with a 1. Inembodiments, the subset of electrical signal features having radii ofinfluence encompassing a vertex may be referred to as an influencesubset. In embodiments, though some vertices may be labeled with a 1multiple times (e.g., where the vertices fall within more than one radiiof influence), those vertices may retain the label of I.

Embodiments of the method 600 may further include determining the numberof mesh vertices of the mesh element that are labeled with the secondvalue (block 610), and apply presentation effects to the mesh based onthe determined number. For example, as shown in FIG. 6, embodiments ofthe method 600 may include applying a highlighting effect, but no bordereffect, to a mesh element if the number of mesh vertices of the meshelement that are labeled with the second value is 3 (block 612). Asshown in FIGS. 6 and 7, embodiments of the method 600 may includeapplying a border effect 702, but no highlighting effect 704, to themesh element (e.g., 706) if the number of mesh vertices of the meshelement that are labeled with the second value is 2 (block 614); andapplying no border effect 702 and no highlighting effect 704 to the meshelement if the number of mesh vertices of the mesh element that arelabeled with the second value is less than 2 (block 616). The resultingrepresentation 708 of the ROI may be bounded within the applied bordereffect, which may be presented, for example, as a border, as describedherein (e.g., a white border).

The illustrative method 600 shown in FIG. 6 is not intended to suggestany limitation as to the scope of use or functionality of embodiments ofthe present disclosure. Neither should the illustrative method 600 beinterpreted as having any dependency nor requirement related to anysingle aspect or combination of aspects illustrated therein.Additionally, any one or more of the aspects depicted in FIG. 6 may be,in embodiments, integrated with various ones of the other aspectsdepicted therein (and/or components not illustrated), all of which areconsidered to be within the ambit of the present disclosure.

Embodiments of the method 600 described above, with reference to FIGS. 6and 7, may result in highlighted regions that have a more “jagged”appearance, due to the finite resolution of the triangles. Inembodiments, a highlighted region with a more “smooth” appearance may begenerated using embodiments of other methods such as, for example, amethod loosely based on the concept of metaballs. FIG. 8 is a flowdiagram depicting an illustrative method 800 of facilitatingpresentation of cardiac information, in accordance with embodiments ofthe subject matter disclosed herein. FIGS. 9 and 10A-C are conceptualschematic diagrams depicting aspects of an illustrative ROI highlightingoperation, as described in embodiments of the method 800 depicted inFIG. 8, in accordance with embodiments of the subject matter disclosedherein. Aspects of embodiments of the method 800 may be performed, forexample, by a processing unit (e.g., the processing unit 120 depicted inFIG. 1, and/or the processing unit 200 depicted in FIG. 2).

Embodiments of the method 800 include determining, from a plurality ofcardiac electrical signal features extracted from a plurality of cardiacelectrical signals, a set of interesting cardiac electrical signalfeatures (block 802). Embodiments of the method 800 further includedetermining a radius of influence of each interesting cardiac electricalsignal feature (block 804). As shown, embodiments of the method 800include determining a position (e.g., P, depicted in FIG. 9) of eachmodel pixel (block 806) and determining, for each model pixel, aninfluence subset of the set of interesting cardiac electrical signalfeatures (block 808). An influence subset of the set of interestingcardiac electrical signal features may include, for example, eachinteresting cardiac electrical signal feature having a radius ofinfluence that encompasses or otherwise affects a given pixel. Inembodiments, for example, each electrical signal feature in theinfluence subset may be denoted as e_(i), wherein 1=1, . . . , N.

Embodiments of the method 800 further include determining, for eachmodel pixel, an influence force, f_(i), associated with each cardiacelectrical signal feature of the influence subset (block 810). Inembodiments, for example, the influence force, f_(i), may be a functionof the electrical signal feature's position and P: f_(i)=g(e_(i),P),where g is some function that is dependent upon a surface distance,surf_dist, between e_(i) and P. For example, in embodiments, g=1/surfdist(e_(i),P). Surface distance may be determined (e.g., approximated)using any number of different techniques. In embodiments, as depictedfor example, in FIG. 9, surface distance may be approximated by, basedon normals 900, 902, and 904 to the mesh 906 corresponding to thepositions associated with the features, e_(i), and P, drawing an arc 908such that the slope of the arc 908 at the two endpoints is perpendicularto the respective normals 900 and 902. The length of the arc 980 may beused as an approximation of the surface distance. In embodiments, thisapproximation of surface distance may be configured to be more accurateby using small radii of influence such that the curvature between thetwo endpoints is reduced.

According to embodiments, the method 800 may include determining, foreach model pixel, a sum, F, of the influence forces (block 812):F=sum(f(e_(i),P)) for each i. The method 800 may include comparing, foreach model pixel, the sum, F, of the influence forces to a threshold, TH(block 814); and applying a highlighting effect to each model pixel ifthe sum, F, of the influence forces exceeds the threshold, TH (block816) (F>TH); and not applying a highlighting effect if the sum, F, doesnot exceed the threshold, TH (block 818) (F<=TH).

In embodiments, the method 800 may include creating a border (not shownin FIG. 8, but conceptualized in FIGS. 10A-C). A border may be createdusing any number of different techniques. According to embodiments, forexample, the border may be created by generating a shape 1000, using thehighlighted pixels 1010, where the shape 1000 is expanded in size (e.g.,by scaling, by a small factor, each highlighted pixel along the mesh'scurvature). The shape may be rendered behind the highlighted pixels 1010(e.g., as a layered effect, beneath the highlighted pixels), therebyresulting in a border 1020. In embodiments, although the shape 1010 andresulting border 1020 are depicted, in FIGS. 10B-C, for purposes ofclarity of description, as being colored black, the shape 1010 andresulting border 1020 may be rendered in any number of different colorssuch as, for example, in white.

The illustrative method 800 shown in FIG. 8 is not intended to suggestany limitation as to the scope of use or functionality of embodiments ofthe present disclosure. Neither should the illustrative method 800 beinterpreted as having any dependency nor requirement related to anysingle aspect or combination of aspects illustrated therein.Additionally, any one or more of the aspects depicted in FIG. 8 may be,in embodiments, integrated with various ones of the other aspectsdepicted therein (and/or components not illustrated), all of which areconsidered to be within the ambit of the present disclosure.

Various modifications and additions can be made to the exemplaryembodiments discussed without departing from the scope of the presentdisclosure. For example, while the embodiments described above refer toparticular features, the scope of this disclosure also includesembodiments having different combinations of features and embodimentsthat do not include all of the described features. Accordingly, thescope of the present disclosure is intended to embrace all suchalternatives, modifications, and variations as fall within the scope ofthe claims, together with all equivalents thereof.

We claim:
 1. A system for facilitating display of cardiac information,the system comprising: a display device configured to present a cardiacmap; and a processing unit configured to: receive a plurality ofelectrical signals; receive an indication of a measurement locationcorresponding to each electrical signal of the plurality of electricalsignals; generate, based on the plurality of electrical signals, thecardiac map, the cardiac map comprising a plurality of annotationsrepresenting a plurality of cardiac signal features; determine, from theplurality of cardiac signal features, a set of interesting cardiacsignal features; determine, based on the set of interesting cardiacsignal features, a region of interest; and facilitate display, via thedisplay device, of the cardiac map and a representation of the region ofinterest, the representation of the region of interest comprising afirst display parameter value that is different from a second displayparameter value, wherein the second display parameter value isassociated with at least one cardiac signal feature that is not includedwithin the region of interest.
 2. The system of claim 1, wherein theprocessing unit is further configured to: determine, for each cardiacsignal feature of the set of cardiac signal features, a radius ofinfluence; and determine the region of interest based on the determinedradius of influence for each cardiac signal feature.
 3. The system ofclaim 2, wherein the processing unit is configured to generate thecardiac map based on a mesh, and wherein the processing unit is furtherconfigured to: label each mesh vertex of a mesh element of the mesh witha first value; label each mesh vertex of the mesh element of the meshwith second value if a criterion is satisfied; and facilitate display ofthe representation of the region of interest based on the mesh vertexlabels.
 4. The system of claim 3, wherein the mesh comprises atriangular mesh, wherein the first value comprises a 0, and wherein thesecond value comprises a 1, and wherein the processing unit isconfigured to: determine the number of mesh vertices of the mesh elementthat are labeled with the second value; apply a highlighting effect, butno border effect, to the mesh element if the number of mesh vertices ofthe mesh element that are labeled with the second value is 3; apply aborder effect, but no highlighting effect, to the mesh element if thenumber of mesh vertices of the mesh element that are labeled with thesecond value is 2; and apply no border effect and no highlighting effectto the mesh element if the number of mesh vertices of the mesh elementthat are labeled with the second value is less than
 2. 5. The system ofclaim 2, wherein the processing unit is further configured to: determinea position of each model pixel; determine, for each model pixel, aninfluence subset of the set of interesting cardiac electrical signalfeatures; determine, for each model pixel, an influence force associatedwith each cardiac electrical signal feature of the influence subset;determine, for each model pixel, a sum of the influence forces; compare,for each model pixel, the sum of the influence forces to a threshold;and apply a highlighting effect to each model pixel if the sum of theinfluence forces exceeds the threshold.
 6. The system of claim 5, thecardiac electrical signal feature comprising at least one of anactivation time, a detected activation, a minimum voltage value, amaximum voltages value, a maximum negative time-derivative of voltage,an instantaneous potential, a voltage amplitude, a dominant frequency,and a peak-to-peak voltage.
 7. The system of claim 6, the displayparameter comprising color saturation.
 8. The system of claim 7, whereinthe color saturation associated with the region of interest is differentthan the color saturation value associated with regions outside of theregion of interest.
 9. The system of claim 6, wherein the set ofinteresting cardiac signal features is user selectable.
 10. A system forfacilitating display of cardiac information, the system comprising: adisplay device configured to present a cardiac map; and a processingunit configured to: receive a plurality of electrical signals; receivean indication of a measurement location corresponding to each electricalsignal of the plurality of electrical signals; generate, based on theplurality of electrical signals, the cardiac map, the cardiac mapcomprising a plurality of annotations representing a plurality ofcardiac signal features; determine, from the plurality of cardiac signalfeatures, a set of interesting cardiac signal features; determine, foreach cardiac signal feature of the set of cardiac signal features, aradius of influence; determine, based on the set of interesting cardiacsignal features and the corresponding radii of influence, a region ofinterest; and facilitate display, via the display device, of the cardiacmap and a representation of the region of interest.
 11. The system ofclaim 10, the representation of the region of interest comprising afirst color saturation value that is different from a second colorsaturation value, wherein the second color saturation value isassociated with at least one cardiac signal feature that is not includedwithin the region of interest.
 12. The system of claim 11, the cardiacelectrical signal feature comprising at least one of an activation time,a detected activation, a minimum voltage value, a maximum voltagesvalue, a maximum negative time-derivative of voltage, an instantaneouspotential, a voltage amplitude, a dominant frequency, and a peak-to-peakvoltage.
 13. The system of claim 12, wherein the set of interestingcardiac signal features is user selectable.
 14. A system forfacilitating display of cardiac information, the system comprising: adisplay device configured to present a cardiac map; and a processingunit configured to: receive a plurality of electrical signals; receivean indication of a measurement location corresponding to each electricalsignal of the plurality of electrical signals; generate, based on theplurality of electrical signals, the cardiac map, the cardiac mapcomprising a plurality of annotations representing a plurality ofcardiac signal features; determine, from the plurality of cardiac signalfeatures, a set of interesting cardiac signal features; determine, foreach cardiac signal feature of the set of cardiac signal features, aradius of influence; determine, based on the set of interesting cardiacsignal features and the corresponding radii of influence, a region ofinterest; and facilitate display, via the display device, of the cardiacmap and a representation of the region of interest.
 15. The system ofclaim 14, the representation of the region of interest comprising afirst color saturation value that is different from a second colorsaturation value, wherein the second color saturation value isassociated with at least one cardiac signal feature that is not includedwithin the region of interest.
 16. The system of claim 14, wherein theprocessing unit is configured to generate the cardiac map based on amesh, and wherein the processing unit is further configured to: labeleach mesh vertex of a mesh element of the mesh with a first value; labeleach mesh vertex of the mesh element of the mesh with second value if acriterion is satisfied; and facilitate display of the representation ofthe region of interest based on the mesh vertex labels.
 17. The systemof claim 16, wherein the mesh comprises a triangular mesh, wherein thefirst value comprises a 0, and wherein the second value comprises a 1,and wherein the processing unit is configured to: determine the numberof mesh vertices of the mesh element that are labeled with the secondvalue; apply a highlighting effect, but no border effect, to the meshelement if the number of mesh vertices of the mesh element that arelabeled with the second value is 3; apply a border effect, but nohighlighting effect, to the mesh element if the number of mesh verticesof the mesh element that are labeled with the second value is 2; andapply no border effect and no highlighting effect to the mesh element ifthe number of mesh vertices of the mesh element that are labeled withthe second value is less than
 2. 18. The system of claim 14, wherein theprocessing unit is further configured to: determine a position of eachmodel pixel; determine, for each model pixel, an influence subset of theset of interesting cardiac electrical signal features; determine, foreach model pixel, an influence force associated with each cardiacelectrical signal feature of the influence subset; determine, for eachmodel pixel, a sum of the influence forces; compare, for each modelpixel, the sum of the influence forces to a threshold; and apply ahighlighting effect to each model pixel if the sum of the influenceforces exceeds the threshold.
 19. The system of claim 14, the cardiacelectrical signal feature comprising at least one of an activation time,a detected activation, a minimum voltage value, a maximum voltagesvalue, a maximum negative time-derivative of voltage, an instantaneouspotential, a voltage amplitude, a dominant frequency, and a peak-to-peakvoltage.
 20. The system of claim 19, wherein the set of interestingcardiac signal features is user selectable.